About the role:
CrowdStrike’s Data Science team sits at the exciting intersection of Machine Learning, Big Data, and Security. We are responsible for developing and improving the malware detection capabilities by employing cutting edge Machine Learning techniques. We are looking for a highly motivated Applied Machine Learning Engineer to help us grow our team.
The Applied Machine Learning Engineer is responsible for developing production ML models, as well as services and tools which will be used in fine-tuning detections within our platform, so that we can provide high quality and high fidelity detections to our customers. Additionally, you will aid in our continuous efforts of improving our Machine Learning algorithms, by reviewing their outputs and making the necessary changes.
What You'll Do:
Work with a team of threat researchers, data scientists, and engineers to create technology and proof of concepts for detection and prevention of current and future threats
Create predictive models from scratch using supervised, semi-supervised or unsupervised learning techniques to detect and stop the most sophisticated threats
Identify and prevent adversarial attacks on ML solutions
Develop tools for task automation and services for ML model testing.
Contribute to parsers and feature extraction tools.
What You'll Need:
Sound understanding of standard ML algorithms, their trade-offs, their usage, and how to tune them
Proven experience in developing automation tools and services. Strong fundamentals in problem solving and algorithm design.
Strong programming and scripting skills. Ability to dive into large Python codebases
Proven track record in technically leading projects and mentoring junior team members
Strong communication and presentation skills
Comfortable to work on very large data sets of sparse high dimensional data; experience in pre-processing and analyzing such data to gain actionable insights
Independent self-starter who likes to take ownership and independently seeks out new challenges; Curious and methodic, always looking to identify opportunities for improvement and contributing in that direction.
Bonus Points:
Fundamental understanding of file formats (PE, Mach-o, ELF, PDF, etc.)
Experience with Rust programming.
Familiarity with Linux, Docker, Jenkins, Kubernetes and Git
Experience with developing large scale distributed systems
BA/BS or MA/MS degree or equivalent experience in Computer Science, Information Security, Machine Learning.
